Capstone: Vision-Selected Road Runner Auto

Build the full autonomous stack.

Module 15: Season Robot CapstonesCapstone

In this lesson, you will:

01Select branch from vision.
02Run Road Runner actions.
03Use fallback and telemetry.

Concept narrative

This is the final autonomous proof: a camera result chooses a Road Runner action sequence that uses reusable mechanism actions and safe fallback behavior.

Robot mental model

Every subsystem contributes: hardware class, vision processor, drive localization, Road Runner actions, mechanism states, telemetry, and Git workflow.

Implementation walkthrough

Test each layer alone, then combine. The full auto should report selected branch, pose, active action, mechanism state, and fallback reason.

AutoCapstone.javaJava

PropPosition result = vision.getResultOrDefault();
Action auto = autoFactory.build(result);
Actions.runBlocking(auto);

Common mistakes and debugging

If full auto fails, isolate one layer. Never tune Road Runner and vision thresholds at the same time.

Checkpoint

Fallback is safe.
Each branch is tested.
Validation checklist is complete.
The test record includes the setup, prediction, and observed result.
A teammate can repeat the check from the saved evidence without guessing.

Reflection check

Check your understanding before moving on.

Which result best demonstrates completion of “Capstone: Vision-Selected Road Runner Auto”?

Why record the test setup, prediction, and observed result?

0 of 2 answered

References

Road Runner CENTERSTAGE Auto GuideFull autonomous organization using actions and trajectories.Road Runner 1.0 ActionsAction composition, custom actions, and autonomous structure.FTC VisionPortal DocsOfficial FTC camera and processor lifecycle documentation.